Like the N-convex algorithm, this algorithm attempts to find a set of candidates whose centroid is close to . The key difference is that instead of taking unique candidates, we allow candidates to populate the set multiple times. The result is that the weight of each candidate is simply given by its frequency in the list, which we can then index by random selection:
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再后来，那条小巷的大多数人都搬走了。我们家是最先搬走的，把房子卖了，我在外地读了几年书，又到了教育资源更好的隔壁市。很久很久没再回到县城，我与当初的小伙伴失去了联系。有人搬去了市区，有人搬进了高楼，有人去了大城市，后来听说前院的阿姨去世了。